docstr: For each data transformer in the pipeline, inverse-transform data. Then inverse transformed data is passed to
  the next transformer. Transformers are traversed in reverse order. Raises value error if not all of the
  transformers are invertible and ``partial`` is set to False. Set ``partial`` to True for inverting only the
  InvertibleDataTransformer in the pipeline.
  
  Parameters
  ----------
  data
      (Sequence of) TimeSeries to be inverse transformed.
  partial
      If set to `True`, the inverse transformation is applied even if the pipeline is not fully invertible,
      calling `inverse_transform()` only on the `InvertibleDataTransformer`s
  
  Returns
  -------
  Union[TimeSeries, Sequence[TimeSeries]]
      Inverse transformed data.
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code: def inverse_transform(
      self,
      data: Union[TimeSeries, Sequence[TimeSeries]],
      partial: bool = False,
  ) -> Union[TimeSeries, Sequence[TimeSeries]]:
      """
      For each data transformer in the pipeline, inverse-transform data. Then inverse transformed data is passed to
      the next transformer. Transformers are traversed in reverse order. Raises value error if not all of the
      transformers are invertible and ``partial`` is set to False. Set ``partial`` to True for inverting only the
      InvertibleDataTransformer in the pipeline.
  
      Parameters
      ----------
      data
          (Sequence of) TimeSeries to be inverse transformed.
      partial
          If set to `True`, the inverse transformation is applied even if the pipeline is not fully invertible,
          calling `inverse_transform()` only on the `InvertibleDataTransformer`s
  
      Returns
      -------
      Union[TimeSeries, Sequence[TimeSeries]]
          Inverse transformed data.
      """
      if not partial:
          raise_if_not(
              self._invertible,
              "Not all transformers in the pipeline can perform inverse_transform",
              logger,
          )
  
          for transformer in reversed(self._transformers):
              data = transformer.inverse_transform(data)
          return data
      else:
          for transformer in reversed(self._transformers):
              if isinstance(transformer, InvertibleDataTransformer):
                  data = transformer.inverse_transform(data)
          return data
  
file_path: darts/darts/dataprocessing/pipeline.py
imports: from copy import deepcopy
  from typing import Iterator, Sequence, Union
  from darts import TimeSeries
  from darts.dataprocessing.transformers import BaseDataTransformer, FittableDataTransformer, InvertibleDataTransformer
  from darts.logging import get_logger, raise_if_not
label_desc: Use image node_id 5 for calling the Pipeline obj's underlying member method code with example usage: obj.inverse_transform(data, partial) and returns: data, data